Infrared Thermal Mapping, Analysis and Interpretation in Biomedicine

  • Arul N. Selvan
  • Charmaine ChildsEmail author
Part of the Series in BioEngineering book series (SERBIOENG)


Measurement of body temperature is one of the cornerstones of clinical assessment in medicine. Skin, the largest organ of the human body, is essentially a temperature mosaic determined by the rate of blood flow through arterioles and capillaries adjacent to the skin . This makes the conventional methods of ‘spot’ measurement rather limited in providing detailed information of regional skin temperature. Infrared (IR) thermal imaging however has the potential to provide a robust method of surface temperature mapping in disease states where pathology disturbs the ‘normal’ distribution of blood flow to skin. To advance image interpretation from the conventional qualitative narrative to a quantitative and robust system, analytical developments focus on digital images and require computer-aided systems to produce results rapidly and safely. Hierarchical clustering-based segmentation (HCS) provides a generic solution to the complex interpretation of thermal data (pixel by pixel) to produce clusters and boundary regions at levels not discernible by human visual processing. In this chapter, HCS has been used to aid the interpretation of wound images and to identify variations in temperature clusters around and along the surgical wound for their clinical relevance in wound infection .


Infrared Temperature Thermal mapping Wound infection Image analysis Hierarchical Clustering-based Segmentation (HCS) Isotherm Boundary outlining 



Our grateful thanks to Dr. Jon Willmott, Senior Lecturer in Sensor Systems, University of Sheffield UK, for his constructive comments during the preparation of this manuscript.

We would also like to thank the Machine Learning and Signal Processing Group, Centre of Telecommunication Research and Innovation (CeTRI), Universiti Teknikal Malaysia, Melaka (UTeM) for their contribution in providing the service of their High Performance RAM farm system for processing the thermal images.


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© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Materials and Engineering Research InstituteSheffield Hallam UniversityCity CampusUK
  2. 2.Centre for Health and Social Care ResearchSheffield Hallam UniversitySheffieldUK

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